{"title":"工程管理中数字阴影的推导方法","authors":"G. Schuh, C. Dölle, Christian Tönnes","doi":"10.1109/TEMSCON.2018.8488412","DOIUrl":null,"url":null,"abstract":"Today's manufacturing companies are facing the influences of a dynamic environment due to new technologies, unstable markets as well as unknown political influences. The influences of those factors combined with the effort of reducing the time to market and a more efficient product development requires many decisions and therefore analyses on the management level especially within the engineering department. Most companies store a unique set of information regarding their markets, customers, products and operation systems in numerous databases. That data basis can deliver a valuable insight for supporting decisions and planning activities. Even though the concept of creating a multi-perspective and database overarching information model of products or production systems is discussed since the conception of digital twins, most companies are lacking such an approach. Instead of developing an additional database, which contains all existing information, a methodology for setting up a digital shadow is proposed. Such a model is collecting and merging selected information from existing databases in order to enable real-time data analytics of information that cannot be linked directly due to inconsistency, lack of assignability or lack of transparency. This paper introduces a methodology on how to overcome the described obstacles and how to systematically derive an information model for engineering management, called digital shadow. At first, a framework is set up to identify the individual implementation objectives of a digital shadow. Based on an assignment to certain objectives, different perspectives on the product are derived in order to focus on business environments that require detailed information. Third, the required information are identified systematically and their relations are described. Each business environment represents a system of information in the perspective of a certain stakeholder. In parallel, the existing databases and sources of information are screened. Therefore, the structure is described and evaluated for its utilization within the digital shadow. Finally, the information system is mapped to the structure of existing databases to derive the optimal information structure design for the digital shadow.","PeriodicalId":346867,"journal":{"name":"2018 IEEE Technology and Engineering Management Conference (TEMSCON)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Methodology for the derivation of a digital shadow for engineering management\",\"authors\":\"G. Schuh, C. Dölle, Christian Tönnes\",\"doi\":\"10.1109/TEMSCON.2018.8488412\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Today's manufacturing companies are facing the influences of a dynamic environment due to new technologies, unstable markets as well as unknown political influences. The influences of those factors combined with the effort of reducing the time to market and a more efficient product development requires many decisions and therefore analyses on the management level especially within the engineering department. Most companies store a unique set of information regarding their markets, customers, products and operation systems in numerous databases. That data basis can deliver a valuable insight for supporting decisions and planning activities. Even though the concept of creating a multi-perspective and database overarching information model of products or production systems is discussed since the conception of digital twins, most companies are lacking such an approach. Instead of developing an additional database, which contains all existing information, a methodology for setting up a digital shadow is proposed. Such a model is collecting and merging selected information from existing databases in order to enable real-time data analytics of information that cannot be linked directly due to inconsistency, lack of assignability or lack of transparency. This paper introduces a methodology on how to overcome the described obstacles and how to systematically derive an information model for engineering management, called digital shadow. At first, a framework is set up to identify the individual implementation objectives of a digital shadow. Based on an assignment to certain objectives, different perspectives on the product are derived in order to focus on business environments that require detailed information. Third, the required information are identified systematically and their relations are described. Each business environment represents a system of information in the perspective of a certain stakeholder. In parallel, the existing databases and sources of information are screened. Therefore, the structure is described and evaluated for its utilization within the digital shadow. Finally, the information system is mapped to the structure of existing databases to derive the optimal information structure design for the digital shadow.\",\"PeriodicalId\":346867,\"journal\":{\"name\":\"2018 IEEE Technology and Engineering Management Conference (TEMSCON)\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Technology and Engineering Management Conference (TEMSCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TEMSCON.2018.8488412\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Technology and Engineering Management Conference (TEMSCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TEMSCON.2018.8488412","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Methodology for the derivation of a digital shadow for engineering management
Today's manufacturing companies are facing the influences of a dynamic environment due to new technologies, unstable markets as well as unknown political influences. The influences of those factors combined with the effort of reducing the time to market and a more efficient product development requires many decisions and therefore analyses on the management level especially within the engineering department. Most companies store a unique set of information regarding their markets, customers, products and operation systems in numerous databases. That data basis can deliver a valuable insight for supporting decisions and planning activities. Even though the concept of creating a multi-perspective and database overarching information model of products or production systems is discussed since the conception of digital twins, most companies are lacking such an approach. Instead of developing an additional database, which contains all existing information, a methodology for setting up a digital shadow is proposed. Such a model is collecting and merging selected information from existing databases in order to enable real-time data analytics of information that cannot be linked directly due to inconsistency, lack of assignability or lack of transparency. This paper introduces a methodology on how to overcome the described obstacles and how to systematically derive an information model for engineering management, called digital shadow. At first, a framework is set up to identify the individual implementation objectives of a digital shadow. Based on an assignment to certain objectives, different perspectives on the product are derived in order to focus on business environments that require detailed information. Third, the required information are identified systematically and their relations are described. Each business environment represents a system of information in the perspective of a certain stakeholder. In parallel, the existing databases and sources of information are screened. Therefore, the structure is described and evaluated for its utilization within the digital shadow. Finally, the information system is mapped to the structure of existing databases to derive the optimal information structure design for the digital shadow.